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Building Data Streaming Applications with Apache Kafka

You're reading from   Building Data Streaming Applications with Apache Kafka Design, develop and streamline applications using Apache Kafka, Storm, Heron and Spark

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Product type Paperback
Published in Aug 2017
Publisher Packt
ISBN-13 9781787283985
Length 278 pages
Edition 1st Edition
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Authors (2):
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Chanchal Singh Chanchal Singh
Author Profile Icon Chanchal Singh
Chanchal Singh
Manish Kumar Manish Kumar
Author Profile Icon Manish Kumar
Manish Kumar
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Table of Contents (14) Chapters Close

Preface 1. Introduction to Messaging Systems FREE CHAPTER 2. Introducing Kafka the Distributed Messaging Platform 3. Deep Dive into Kafka Producers 4. Deep Dive into Kafka Consumers 5. Building Spark Streaming Applications with Kafka 6. Building Storm Applications with Kafka 7. Using Kafka with Confluent Platform 8. Building ETL Pipelines Using Kafka 9. Building Streaming Applications Using Kafka Streams 10. Kafka Cluster Deployment 11. Using Kafka in Big Data Applications 12. Securing Kafka 13. Streaming Application Design Considerations

Message producers

In Kafka, the producer is responsible for sending data to the partition of the topic for which it is producing data.

The producer generally does not write data to partitions, it creates write requests for messages and sends them to the leader broker. Partitioner calculates the hash value of the message, which helps the producer to choose which partition should be selected.

The hash value is generally calculated by the message key that we provide when writing the message to a Kafka topic. The message with a null key will be distributed in a round-robin fashion across partitions to ensure even distribution of messages. In Kafka, each partition has a leader and each read write request goes through the leader only. So a request to write messages to a partition of a topic will go through the leader broker. The producer waits for an acknowledgement of messages depending...

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